Iron (II)-based metal-organic framework nanozyme for boosting tumor ferroptosis through inhibiting DNA damage repair and system Xc.

Development of ferroptosis-inducible nanoplatforms with high efficiency and specificity is highly needed and challenging in tumor ferrotherapy. Here, we demonstrate highly effective tumor ferrotherapy using iron (II)-based metal-organic framework (FessMOF) nanoparticles, assembled from disulfide bonds and ferrous ions. The as-prepared FessMOF nanoparticles exhibit peroxidase-like activity and pH/glutathione-dependent degradability, which enables tumor-responsive catalytic therapy and glutathione depletion by the thiol/disulfide exchange to suppress glutathione peroxidase 4, respectively. Upon PEGylation and Actinomycin D (ActD) loading, the resulting FessMOF/ActD-PEG nanoplatform induces marked DNA damage and lipid peroxidation. Concurrently, we found that ActD can inhibit Xc- system and elicit ferritinophagy, which further boosts the ferrotherapeutic efficacy of the FessMOF/ActD-PEG. In vivo experiments demonstrate that our fabricated nanoplatform presents excellent biocompatibility and a high tumor inhibition rate of 91.89%.

Mitochondrial-Targeted Copper Delivery for Cuproptosis-Based Synergistic Cancer Therapy.

Cuproptosis is dependent on mitochondrial respiration modulation by targeting lipoylated tricarboxylic acid cycle (TCA) cycle proteins, showing great potential in cancer treatment. However, the specific release of copper ions at mitochondrial is highly needed and still a major challenge to trigger cellular cuproptosis. Herein, a metal-organic framework-based nanoplatform (ZCProP) is designed for mitochondrial-targeted and ATP/pH-responsive Cu2+ and prodigiosin release. The released Cu2+ promotes aggregation of lipoylated protein and loss of Fe-S cluster protein, resulting in cell cuproptosis. In the meanwhile, Cu2+ can concert with prodigiosin to induce mitochondrial dysfunction and DNA damage and enhance cell cuproptosis. Furthermore, this nanoplatform has an ability to deplete glutathione, which not only further promotes cuproptosis but also triggers cell ferroptosis by the suppression of glutathione peroxidase 4, an anti-ferroptosis protein. Collectively, the designed ZCProP nanoplatform can responsively release cargos at mitochondrial and realize a conspicuous therapeutic efficacy through a cuproptosis-mediated concerted effect. Along with its excellent biocompatibility, this nanoplatform may provide a novel therapeutic modality paradigm to boost cancer therapeutic strategies based on cuproptosis.

In situ generation of hybrid alginate hydrogels for enhanced breast tumor ferrotherapy through multiplex magnifying redox imbalances.

Ferroptosis has drawn great attention to tumor treatments over the past decade. However, how to specifically boost tumoral redox imbalance by simultaneously superimposing iron-mediated reactive oxygen species and undermining antioxidative pathways at the tumor site is still a significant challenge in ferroptosis-based tumor ferrotherapy. In this study, we designed an in situ generable hydrogel that contains paclitaxel/chlorin e6-loaded iron-based metal-organic framework (Fe-MOF) nanoparticles for enhanced breast tumor ferrotherapy by multiplex magnifying redox imbalance. The polysaccharide sodium alginate can crosslink with tumoral calcium ions to generate a hydrogel patch, which promotes the retention of Fe-MOF and therapeutic molecules. The Fe-MOF holds peroxidase/glutathione oxidase mimicking properties, resulting in OH generation via the Fenton reaction and glutathione consumption. Local ultrasound treatment facilitates the release of therapeutics and stimulates the generation of signet oxygen by activating the sonosensitizer chlorin e6. In the meanwhile, the low-dose paclitaxel reduces tumoral pH value by downregulating the glutaminolysis-related gene (SLC7A11) which in turn enhances the catalytic activity of Fe-MOF and inhibits antioxidative pathways, respectively. Both in vivo and in vitro experiments show that our designed hybrid hydrogels can induce significant ferrotherapeutic effects by augmenting the tumoral oxidative stresses.

Spectral bidirectional texture function reconstruction by fusing multiple-color and spectral images.

Spectral bidirectional texture function (BTF) is essential for accurate reproduction of material appearance due to its nature of conveying both spatial and spectral information. A practical issue is that the acquisition of raw spectral BTFs is time-consuming. To resolve the limitation, this paper proposes a novel framework for efficient spectral BTF acquisition and reconstruction. The framework acquires red-green-blue (RGB) BTF images and just one spectral image. The full spectral BTFs are reconstructed by fusing the RGB and spectral images based on nonnegative matrix factorization (NMF). Experimental results indicate that the accuracy of spectral reflectance reconstruction is higher than that of existing algorithms. With the reconstructed spectral BTFs, the material appearance can be reproduced with high fidelity under various illumination conditions.

Empirical model for matching spectrophotometric reflectance of yarn windings and multispectral imaging reflectance of single strands of yarns.

The state-of-the-art multispectral imaging system can directly acquire the reflectance of a single strand of yarn that is impossible for traditional spectrophotometers. Instead, the spectrophotometric reflectance of a yarn winding, which is constituted by yarns wound on a background card, is regarded as the yarn reflectance in textile. While multispectral imaging systems and spectrophotometers can be separately used to acquire the reflectance of a single strand of yarn and corresponding yarn winding, the quantitative relationship between them is not yet known. In this paper, the relationship is established based on models that describe the spectral response of a spectrophotometer to a yarn winding and that of a multispectral imaging system to a single strand of yarn. The reflectance matching function from a single strand of yarn to corresponding yarn winding is derived to be a second degree polynomial function, which coefficients are the solutions of a constrained nonlinear optimization problem. Experiments on 100 pairs of samples show that the proposed approach can reduce the color difference between yarn windings and single strands of yarns from 2.449 to 1.082 CIEDE2000 units. The coefficients of the optimal reflection matching function imply that the reflectance of a yarn winding measured by a spectrophotometer consists of not only the intrinsic reflectance of yarn but also the nonignorable interreflection component between yarns.

Channel selection for multispectral color imaging using binary differential evolution.

In multispectral color imaging, there is a demand to select a reduced number of optimal imaging channels to simultaneously speed up the image acquisition process and keep reflectance reconstruction accuracy. In this paper, the channel selection problem is cast as the binary optimization problem, and is consequently solved using a novel binary differential evolution (DE) algorithm. In the proposed algorithm, we define the mutation operation using a differential table of swapping pairs, and deduce the trial solutions using neighboring self-crossover. In this manner, the binary DE algorithm can well adapt to the channel selection problem. The proposed algorithm is evaluated on the multispectral color imaging system on both synthetic and real data sets. It is verified that high color accuracy is achievable by only using a reduced number of channels using the proposed method. In addition, as binary DE is a global optimization algorithm in nature, it performs better than the traditional sequential channel selection algorithm.

Reversible mechanochromism of a luminescent elastomer.

A novel mechanochromic elastomer was manufactured by doping bis(benzoxazolyl)stibene (BBS) into a thermoplastic polyurethane. Both solution casting and melt compounding approaches were tried with a range of BBS concentrations, and an optimal concentration of 0.5% was selected to investigate the mechanochromic mechanism in detail. When the blend film was stretched up to 100%, its emission peaks at 475 and 413 nm changed in intensity ratio from 6.3 to 1.8. When it was released, both the film size and emission peaks largely recovered. By a short annealing at 120 °C, their full recovery was achieved. Its reversion mechanism was proposed and proved by X-ray diffraction. In comparison to previous mechanochromic materials, this smart elastomer is easy to prepare, highly sensitive to stress, facilely renewable in usage, and totally based on biocompatible materials, having potential applications like stress sensors, intelligent devices, and alarming packages.

Autofocus for multispectral camera using focus symmetry.

A multispectral camera acquires spectral color images with high fidelity by splitting the light spectrum into more than three bands. Because of the shift of focal length with wavelength, the focus of each channel should be mechanically adjusted in order to obtain sharp images. Because progressive adjustment is quite time consuming, the clear focus must be determined by using a limited number of images. This paper exploits the symmetry of focus measure distribution and proposes a simple yet efficient autofocus method. The focus measures are computed using first-order image derivatives, and the focus curve is obtained by spline interpolation. The optimal focus position, which maximizes the symmetry of the focus measure distribution, is then computed according to distance metrics. The effectiveness of the proposed method is validated in the multispectral camera system, and it is also applicable to relevant imaging systems.

Optimal selection of representative colors for spectral reflectance reconstruction in a multispectral imaging system.

In a multispectral color imaging system, the spectral reflectance of the object being imaged always needs to be accurately reconstructed by employing the training samples on specific color charts. Considering that the workload is heavy when all those color samples are used in practical applications, it is important to select only a limited number of the most representative samples. This is possible as the color charts are usually designed to cover the range of commonly imaged colors, and the color samples are redundant for spectral image reconstruction. We propose an eigenvector-based method and a virtual-imaging-based method for representative color selection by minimizing the total reflectance root-mean-squares errors. The effectiveness of the proposed methods is confirmed by experimental results when compared with existing techniques.

Improved reflectance reconstruction for multispectral imaging by combining different techniques.

In multispectral imaging system, one of the most important tasks is to accurately reconstruct the spectral reflectance from system responses. We propose such a new method by combing three most frequently used techniques, i.e., wiener estimation, pseudo-inverse, and finite-dimensional modeling. The weightings of these techniques are calculated by minimizing the combined standard deviation of both spectral errors and colorimetric errors. Experimental results show that, in terms of color difference error, the performance of the proposed method is better than those of the three techniques. It is found that the simple averaging of the reflectance estimates of these three techniques can also yield good color accuracy.

Reflectance reconstruction for multispectral imaging by adaptive Wiener estimation.

In multispectral imaging, Wiener estimation is widely adopted for the reconstruction of spectral reflectance. We propose an improved reflectance reconstruction method by adaptively selecting training samples for the autocorrelation matrix calculation in Wiener estimation, without a prior knowledge of the spectral information of the samples being imaged. The performance of the proposed adaptive Wiener estimation and the traditional method are compared in the cases of different channel numbers and noise levels. Experimental results show that the proposed method outperforms the traditional method in terms of both spectral and colorimetric prediction errors when the imaging channel number is 7 or less. When the imaging system consists of 11 or more channels, the color accuracy of the proposed method is slightly better than or becomes close to that of the traditional method.